Top 7 Radiology Artificial Intelligence Tools

Are you aware that AI is powering the radiology industry? Do you know that artificial intelligence can provide you with efficient medical imaging software? The purpose of artificial intelligence in healthcare is to improve how health information and patient care are managed. It uses techniques like diagnosis, patient prognosis, treatment planning, and AI algorithms to simplify data interpretation and improve diagnostic processes.

Artificial intelligence provides health professionals with substantial data and radiology reports to deliver the right treatment, making personalized healthcare accessible to individuals. This article will enlighten you on the top seven AI software tools you can use to enhance radiology.

What is Artificial Intelligence?

Artificial Intelligence (AI) is the use of machines and algorithms to imitate human reasoning. It uses software to replicate the human intellectual process. AI is used globally by different sectors of the economy.

The use of AI in  Healthcare  dates back to the 1960s and 1970s when the organic chemistry solution program was developed. It was used with Mycin to treat bacterial infections.

AI helps avoid traditional methods of treatment by providing better ways to diagnose and treat patients. The power of AI in healthcare lies in its ability to analyze large amounts of information and give useful feedback to health practitioners. Deep learning, a subset of AI, plays a crucial role in radiology by enhancing image reconstruction, improving diagnostic accuracy, and automating various tasks.

For example, in ultrasound, AI assesses images and interprets the information for sonographers. It uses machine learning and programming to produce an output. AI-generated information can be used to prevent diseases and alleviate patient suffering.

Application of AI in Medical Imaging in Healthcare

 AI health systems  use machine learning and natural language processing to analyze health conditions and predict patient outcomes. Integrating AI solutions into the clinical workflow is crucial for ensuring seamless adoption and financial viability within the clinical routine. Applications of AI in radiology healthcare include:

Mammography

Research shows that doctors miss 40% of breast tumors during checkups. AI in radiology helps in breast assessments to find lesions and abnormalities, checking for malignant and benign tumors, and estimating breast density.

Neuroradiology

Identifies lesions, stroke aneurysms, and bleeding. Determines brain structures and annotates cortical structures.

Fracture Identification

AI and radiology detect broken bones in the hand, hips, and wrists. This is especially useful for diagnosing fractures in the elderly, which often hide under soft tissues. Artificial intelligence radiology makes these fractures visible for easy treatment.

Brain Tumors

Before the advancement of artificial intelligence in radiology, doctors and patients could not characterize brain tumors before surgery. Artificial intelligence for radiology provides timely insights and necessary information to prepare doctors for surgery.

Lung Cancer

AI radiology screens and characterizes lung tumors early, identifying subtle signs of cancer. It improves diagnostic accuracy and treatment to enhance patient outcomes.

Abdominal Radiology

AI helps in partitioning liver images and genitourinary structures. Radiology and AI detect lesions and blood clots in the lungs and identify liver and kidney lesions.

Chest Radiology

Highlights lung masses, inflammation, and broken ribs. Artificial intelligence and radiology detect fluid-filled lungs, lung impediments, and air-filled lungs.

Cardiovascular Radiology

Analyzes blood vessel imaging, heart blockages, and heart conditions. It also diagnoses heart muscle diseases and predicts patient outcomes.

Musculoskeletal Radiology

Determines broken bones in the upper limb, such as the humerus, ankle, wrist, and hand. It analyzes hip bone weakness and checks bone quality.

Tumor Radiology

Identifies tumors, lung masses, and tumor outlines. AI determines whether lung tumors are benign or malignant.

Head and Neck

Radiology and artificial intelligence outline lesions to locate them accurately. It partitions, characterizes, and quantifies head tumors and lymph nodes.

Mouth and Maxillofacial

Detects tooth decay, diseases, and fractures. Identifies jaw bone tumors and irregularities in teeth alignment. It also analyzes artificial teeth implants.

Top 7 AI Tools for Radiology

 Radiobotics 

Radiobotics is a Danish company using artificial intelligence to perform X-rays in minutes. AI systems in radiology can create detailed narrative reports and face challenges such as data curation and ethical issues related to patient data. These X-rays detect fractures early, preventing the risks associated with missed fractures. They help determine hip dysplasia and pinpoint potential conditions that can be prevented. Radiobotics provides proven and tested opinions for healthcare providers.

The fractures identified are mostly in long bones like the leg, elbow, wrist, foot, hip, knee, and lower leg. It also identifies fluid in the elbow and knee. Radiobotics not only gives accurate fracture diagnoses but also detects and classifies osteoarthritis. It helps automate strenuous tasks, saving time and energy, and prevents risks like increased costs and patient discomfort from complications.

Key Solutions

• Fractures: Detection and localization of broken bones, accurately identifying lipohemarthrosis.
• Knee: Classification of knee defects and checking for abnormalities like joint distance narrowing and sclerosis.
• Hip: Quantification of bone weakness, measuring the degree of hip dysplasia, alpha angle, LCE (Lateral Center Edge) angle, and Minimum Femoroacetabular Joint Space Width in mm, plus the obturator index.

The benefits of human-AI interaction in these diagnostic processes include improved accuracy and efficiency, ultimately enhancing patient outcomes.

Companies Partnering with Radiobotics

• Lunit
• Blackford
• Deepc
• Vrad
• TeleRay
• ImageBiopsy

 Myrian 

Myrian is AI for radiology software that assists with clinical examinations.

Key Features

• Prostate: Uses software to check liver, prostate, oncology, and abdominal fat. Enables identification and measurement of lesions and calculation of PSA values. Efficiently detects and localizes prostate cancer in patients.
• XP Lungs: Speeds up patient follow-up with strategic analysis. Aligns with MRI (Magnetic Resonance Imaging), CT, and PET-CT. Identifies, assesses, and measures pulmonary lesions. Monitors, classifies, and measures lung nodules. Calculates nodule multiplication and growth rate. Provides synchronized images from examinations and 3D images of lesions.
• XP Colon: Offers a detailed view of the colon during screening. Identifies abnormal growth in the mucous membrane of the colon. Measures lesions in the rectum and provides 3D views and fat evaluation. Uses C-RADS (Colonography Reporting and Data System) to evaluate polyps, simplifying work procedures.
• XP Abdofat: Enhances pinpointing of adipose tissue in the abdomen. Provides the ratio of adipose tissue in superficial and deep locations. Measures waist perimeter and provides waist threshold levels. Supplies reports on fat tissue.
• XP Liver: Identifies hepatic lesions and images liver structures. Prepares for hepatectomy by classifying healthy and diseased liver parts.
• Brain: Analyzes the brain to make instant diagnosis for stroke patients.

Myrian is also capable of generating radiology reports, improving collaboration and communication between medical professionals.

 Carebot 

Carebot operates on the premise that artificial intelligence can provide patients with quality care. It speeds up recovery by identifying health challenges and giving insights to doctors. This allows doctors to use this data to treat individuals and helps healthcare providers attend to a large number of patients in a short period. Key features include:

• CXR (Chest X-Ray): Carebot uses AI-engineered X-rays to view and evaluate the organs in your chest. This process can detect cancerous cells early, alerting your doctor to start treatments. The accuracy of doctors in locating lesions is 57%, while AI achieves 82%. Mass detection by doctors is 67%, while AI reaches 89%. With these numbers, doctors using AI tools have a 25% higher success rate in diagnosis.
• MMG (Mammography): Carebot performs examinations on the human breast to detect tumors. It provides insights for doctors to diagnose breast cancer and start treatments, achieving a 99% survival rate. Carebot likely ensures more than 5 years of survival after early breast cancer detection, and early detection reduces treatment costs.

 Jazz 

Jazz is a user-friendly AI software that tracks lesions. Once it identifies a lesion, it will never forget it. It is the best AI tool for detecting multiple sclerosis and malignant tumors. Its functions include the detection, measurement, and annotation of lesions. Jazz is also used for conducting MRI and ultrasound scans, providing analysis within three minutes, which increases work output and quality.

Jazz is set to enhance its data strategy and has partnered with the global company TenX. This partnership will power its data system with EFS (Enterprise Future Store) and predictive models. Jazz is intuitive software for radiologists, easing the process of manual lesion detection.

Jazz is used by:

• Medical doctors
• Radiologists
• Neuroradiologists
• Medical imaging professionals
• Health professionals
• Cancer specialists
• Radiation oncologists

 Rayvolve 

Rayvolve is AI-driven software that performs X-ray analysis. Owned by Azmed company, it uses machine learning to identify bone fractures, providing 20% more accurate results and reducing false negatives by 67%. It also offers 96% sensitivity and 86% specificity in X-ray tests.

Rayvolve yields quick results, alleviating patient discomfort and saving healthcare providers 27% of the time on injury X-rays and 36% on chest X-rays. It is used in 33 countries across 5 continents. Azmed has partnered with GE Healthcare to promote AI awareness in healthcare.

Use Cases

• General Routine Inspection: Determines cases that require special attention.
• Childcare: Helps detect fractures in children.
• Emergency Conditions: Used in accidents to detect fractures. Rayvolve also excels in analyzing medical images, enhancing the accuracy of radiological assessments.

Benefits of Rayvolve

• For Patients: Alleviates discomfort with timely results, providing real-time treatments. Rayvolve also enhances the detection and classification of breast lesions through screening mammography, utilizing computer-aided detection and deep learning techniques.
• For Health Professionals: Supplies doctors and physicians with accurate and authentic information to treat patients.
• For Health Establishments: Elevates services by utilizing Rayvolve’s capabilities.

 ImageBiopsy Lab 

ImageBiopsy Lab is an AI-powered SaaS company that supports digital musculoskeletal diagnosis. It provides services for the spine, knee, hand, hip, leg, and foot. The software localizes and measures bone fractures while producing high-quality images for guidance. It organizes results in a radiological communication system.

Key Features

• Pediatric Bone Age and Developmental Assessment: Analyzes bone development in children, determining adult height, bone age, and development. It automates the work process, saving time and energy. 93% of health personnel agree that ImageBiopsy Lab benefits medical practice.
• Knee Osteoarthritis Labeling Assistant: Alerts doctors to the severity of knee osteoarthritis with 83% sensitivity and 87% specificity. It provides efficient measurements and X-ray analysis, monitoring osteoarthritis progress and cartilage loss.
• Hip Positioning Assistant: Detects hip impairments early to improve surgery outcomes. It offers reproducible results from hip surgeries, assists with pelvic analysis, and reduces workload, allowing doctors to focus on individual results. Increases productivity and reduces work time by 80%.
• Leg Angle Measurements Assistant: Addresses leg displacement and knee replacement issues, reading leg X-rays and reducing time spent on manual methods. Measures leg parameters to evaluate abnormalities, assists in knee surgeries, foot alignment, and the implantation of artificial knees and hips. Offers a 90% reduction in reading time.
• Flamingo: Detects fractures caused by osteoporosis using CT scans. Identifies vertebral fractures with 80% sensitivity and 98% specificity, preventing missed diagnoses. Provides insights for further treatments. A study by Harvard Medical School validates the tool's effectiveness.

 Qure AI 

Qure AI is an AI SaaS company founded in 2016 by Prashant Warier and Dr. Pooja Rao. It enhances imaging in radiology departments by using machine learning to interpret MRIs, X-rays, ultrasounds, and CT scans. It helps the healthcare industry automate diagnosis with ease and accuracy.

Qure AI detects brain-related injuries and enables health practitioners to conduct quick diagnoses, helping them triage medical problems. It can identify 30 different diseases in a chest X-ray, helping to prevent complications in patients.

Key Features

• QXR: Identifies chest diseases using X-rays, differentiating between normal and diseased chests. Diagnoses tuberculosis and analyzes COVID-19 patients, instantly assessing lung damage.
• QER: Automates head CT scans and provides patient data for further treatments. It is critical in diagnosing traumatic brain injury (TBI). As AI systems, Qure AI's tools enhance the automation of diagnosis, improving efficiency and accuracy.
• qQuant: Uses 3D imaging to monitor the progression of diseases in CT and MRI scans. It is particularly useful in clinical trials of drugs.

Artificial intelligence is making a significant difference in our everyday lives. The healthcare sector is actively embracing artificial intelligence, especially in the radiology department. Radiologists can use AI to improve their work processes and focus more on their patients.